load our R Packages that we will use here.
library(tidyverse)
library(DT)
library(choroplethr)
library(choroplethrMaps)
Superstore= read.csv("SampleSuperstore.csv")
Sales Analysis
Statewise Sales Analysis
Statewise_Sales= Superstore %>%
group_by(State) %>%
summarise(Total_Sales= sum(Sales)) %>%
arrange(desc(Total_Sales))
datatable(Statewise_Sales)
Plotting Statewise Sales Analysis
ggplot(Statewise_Sales,aes(reorder(State,Total_Sales),Total_Sales,fill=State))+
geom_col(width = 0.5, alpha = 0.5)+
geom_point(size=3, color="black",alpha=0.07)+
scale_x_discrete(labels = Statewise_Sales[order(Statewise_Sales$Total_Sales),]$State) +
theme_classic()+
coord_flip()+
geom_text(aes(State,Total_Sales,label =Total_Sales))+
labs(x = "State", y = "Total Sales", title = "Statewise Sales Analysis")+
theme(axis.text = element_text(size = 10, face = "bold"), title = element_text(size = 16))+
theme(legend.title = element_text(size=10),legend.text = element_text(size=10),legend.position="bottom")
Regionwise Sales Analysis
Regionwise_Sales= Superstore %>%
group_by(Region) %>%
summarise(TotalS= sum(Sales)) %>%
arrange(desc(TotalS))
datatable(Regionwise_Sales)
Plotting Regionwise Sales Analysis
ggplot(Regionwise_Sales,aes(reorder(Region,TotalS),TotalS,fill=Region))+
geom_col(width = 0.5, alpha = 0.5)+
geom_point(size=10, color="black",alpha=0.07)+
scale_x_discrete(labels = Regionwise_Sales[order(Regionwise_Sales$TotalS),]$Region) +
theme_classic()+
coord_flip()+
geom_text(aes(Region,TotalS,label =TotalS))+
labs(x = "Region", y = "Total Regionwise Sales", title = "Regionwise Analysis of Sales")+
theme(axis.text = element_text(size = 10, face = "bold"), title = element_text(size = 16))+
theme(legend.title = element_text(size=10),legend.text = element_text(size=10),legend.position="bottom")
Geographic Plots of Statewise Sales Analysis
GSPlot= Superstore %>%
group_by(State) %>%
summarise(Total_Sales= sum(Sales)) %>%
arrange(desc(Total_Sales))
datatable(GSPlot)
Converting into a Geographic Plot
colnames(GSPlot)= c('region', 'value')
GSPlot$region= tolower(GSPlot$region)
we use here library(choroplethr) and library(choroplethrMaps) for map
Plots of Statewise Sales Analysis
state_choropleth(GSPlot,title= "Geographic Analysis of Sales",legend="Sales in USD")
Profit Analysis
Statewise Profit Analysis
Statewise_Profit= Superstore %>%
group_by(State) %>%
summarise(Total_Profit= sum(Profit)) %>%
arrange(desc(Total_Profit))
datatable(Statewise_Profit)
Plotting Statewise Profit Analysis
ggplot(Statewise_Profit, aes(x=State,y=Total_Profit,fill= State)) +
geom_col(width = 0.7, alpha = 0.5)+
geom_point(size=3, color="black",alpha=0.07)+
scale_x_discrete(labels = Statewise_Profit[order(Statewise_Profit$Total_Profit),]$State) +
coord_flip()+
geom_text(aes(State,Total_Profit,label =Total_Profit))+
labs(x = "State", y = "Total Profit", title = "Statewise Profit Analysis")+
theme(axis.text = element_text(size = 10, face = "bold"), title = element_text(size = 16))+
theme(legend.title = element_text(size=10),legend.text = element_text(size=10),legend.position="bottom")
Regionwise Profit Analysis
Regionwise_Profit= Superstore %>%
group_by(Region) %>%
summarise(TotalP= sum(Profit)) %>%
arrange(desc(TotalP))
datatable(Regionwise_Profit)
Plotting Regionwise Profit Analysis
ggplot(Regionwise_Profit, aes(x=Region,y=TotalP,fill= Region)) +
geom_col(width = 0.7, alpha = 0.5)+
geom_point(size=9, color="black",alpha=0.07)+
scale_x_discrete(labels = Regionwise_Profit[order(Regionwise_Profit$TotalP),]$Region) +
theme_classic()+
coord_flip()+
geom_text(aes(Region,TotalP,label =TotalP))+
labs(x = "Region", y = "Total Profit", title = "Statewise Profit Analysis")+
theme(axis.text = element_text(size = 10, face = "bold"), title = element_text(size = 16))+
theme(legend.title = element_text(size=10),legend.text = element_text(size=10),legend.position="bottom")
Geographic Plots of Statewise Sales Analysis
GPPlot= Superstore %>%
group_by(State) %>%
summarise(Total_Profit= sum(Profit)) %>%
arrange(desc(Total_Profit))
datatable(GPPlot)
Converting into a Geographic Plot
colnames(GPPlot)= c('region', 'value')
GPPlot$region= tolower(GPPlot$region)
Plotting Statewise Sales Analysis
state_choropleth(GPPlot,title= "Geographic Analysis of Profit",legend="Profit in USD")
Doing some Statewise Profit/Sales Ratio Analysis
Profit_to_Sales= Superstore %>%
group_by(State) %>%
summarise(Profit_Sales_Ratio= sum(Profit)/sum(Sales)) %>%
arrange(desc(Profit_Sales_Ratio))
datatable(Profit_to_Sales)
Plotting Statewise Profit/Sales Ratio Analysis
ggplot(Profit_to_Sales, aes(x=State,y=Profit_Sales_Ratio,fill= State)) +
geom_bar(stat = "identity",width = 0.7, alpha = 0.5)+
geom_point(size=3, color="black",alpha=0.07)+
scale_x_discrete(labels = Profit_to_Sales[order(Profit_to_Sales$Profit_Sales_Ratio),]$State) +
coord_flip()+
geom_text(aes(State,Profit_Sales_Ratio,label =Profit_Sales_Ratio))+
labs(x = "State", y = "Total Profit", title = "Statewise Profit Analysis")+
theme(axis.text = element_text(size = 10, face = "bold"), title = element_text(size = 16))+
theme(legend.title = element_text(size=10),legend.text = element_text(size=10),legend.position="bottom")
Sales and Profit Analysis Segmentwise
Profit_each_segment= Superstore %>%
group_by(Segment) %>%
summarise(Ratio= sum(Profit)/sum(Sales))%>%
arrange(desc(Ratio))
datatable(Profit_each_segment)
plotting Profit/Sales Ratio Plots for each segment
ggplot(Profit_each_segment, aes(x=Segment,y=Ratio,fill= Segment)) +
geom_col(width = 0.5, alpha = 0.5)+
geom_point(size=9, color="black",alpha=0.07)+
scale_x_discrete(labels = Profit_each_segment[order(Profit_each_segment$Ratio),]$Segment) +
theme_classic()+
coord_flip()+
geom_text(aes(Segment,Ratio,label =Ratio))+
labs(x = "Segment", y = "Total Profit", title = "Statewise Profit Analysis")+
theme(axis.text = element_text(size = 10, face = "bold"), title = element_text(size = 16))+
theme(legend.title = element_text(size=10),legend.text = element_text(size=10),legend.position="bottom")
Profitable Office Supplies in California
Superstore %>%
group_by(Sub.Category) %>%
filter(Category== "Office Supplies" & State== "California" ) %>%
summarise(Total_Profit= sum(Profit)) %>%
ggplot(aes(x= Sub.Category,y=Total_Profit, fill= Sub.Category))+
geom_col(width = 0.5, alpha = 0.5)+
geom_point(size=9, color="black",alpha=0.07)+
theme_classic()+
coord_flip()+
geom_text(aes(x= Sub.Category,y=Total_Profit,label =Total_Profit))+
labs(x = "Sub Category", y = "Total Profit", title = "Profitable Office Supplies in California State")+
theme(axis.text = element_text(size = 10, face = "bold"), title = element_text(size = 16))+
theme(legend.title = element_text(size=10),legend.text = element_text(size=10),legend.position="bottom")
Profitable Office Supplies in New Jersey
Superstore %>%
group_by(Sub.Category) %>%
filter(Category== "Office Supplies" & State== "New Jersey" ) %>%
summarise(Total_Profit= sum(Profit)) %>%
ggplot(aes(x= Sub.Category,y=Total_Profit, fill= Sub.Category))+
geom_col(width = 0.5, alpha = 0.5)+
geom_point(size=9, color="black",alpha=0.07)+
theme_classic()+
coord_flip()+
geom_text(aes(x= Sub.Category,y=Total_Profit,label =Total_Profit))+
labs(x = "Sub Category", y = "Total Profit", title = "Profitable Office Supplies in New Jersey State")+
theme(axis.text = element_text(size = 10, face = "bold"), title = element_text(size = 16))+
theme(legend.title = element_text(size=10),legend.text = element_text(size=10),legend.position="bottom")
Profitable Office Supplies in Connecticut
Superstore %>%
group_by(Sub.Category) %>%
filter(Category== "Office Supplies" & State== "Connecticut" ) %>%
summarise(Total_Profit= sum(Profit)) %>%
ggplot(aes(x= Sub.Category,y=Total_Profit, fill= Sub.Category))+
geom_col(width = 0.5, alpha = 0.5)+
geom_point(size=9, color="black",alpha=0.07)+
theme_classic()+
coord_flip()+
geom_text(aes(x= Sub.Category,y=Total_Profit,label =Total_Profit))+
labs(x = "Sub Category", y = "Total Profit", title = "Profitable Office Supplies in Connecticut State")+
theme(axis.text = element_text(size = 10, face = "bold"), title = element_text(size = 16))+
theme(legend.title = element_text(size=10),legend.text = element_text(size=10),legend.position="bottom")
Profitable Office Supplies in Wisconsin
Superstore %>%
group_by(Sub.Category) %>%
filter(Category== "Office Supplies" & State== "Wisconsin" ) %>%
summarise(Total_Profit= sum(Profit)) %>%
ggplot(aes(x= Sub.Category,y=Total_Profit, fill= Sub.Category))+
geom_col(width = 0.5, alpha = 0.5)+
geom_point(size=9, color="black",alpha=0.07)+
theme_classic()+
coord_flip()+
geom_text(aes(x= Sub.Category,y=Total_Profit,label =Total_Profit))+
labs(x = "Sub Category", y = "Total Profit", title = "Profitable Office Supplies in Wisconsin State")+
theme(axis.text = element_text(size = 10, face = "bold"), title = element_text(size = 16))+
theme(legend.title = element_text(size=10),legend.text = element_text(size=10),legend.position="bottom")
Profitable Office Supplies in Colorado
Superstore %>%
group_by(Sub.Category) %>%
filter(Category== "Office Supplies" & State== "Colorado" ) %>%
summarise(Total_Profit= sum(Profit)) %>%
ggplot(aes(x= Sub.Category,y=Total_Profit, fill= Sub.Category))+
geom_col(width = 0.5, alpha = 0.5)+
geom_point(size=9, color="black",alpha=0.07)+
coord_flip()+
geom_text(aes(x= Sub.Category,y=Total_Profit,label =Total_Profit))+
labs(x = "Sub Category", y = "Total Profit", title = "Profitable Office Supplies in Colorado State")+
theme(axis.text = element_text(size = 10, face = "bold"), title = element_text(size = 16))+
theme(legend.title = element_text(size=10),legend.text = element_text(size=10),legend.position="bottom")
Profitable Furnitures in California
Superstore %>%
group_by(Sub.Category) %>%
filter(Category== "Furniture" & State== "California") %>%
summarise(Total_Profit= sum(Profit)) %>%
ggplot(aes(x= Sub.Category,y=Total_Profit, fill= Sub.Category))+
geom_col(width = 0.5, alpha = 0.5)+
geom_point(size=9, color="black",alpha=0.07)+
coord_flip()+
geom_text(aes(x= Sub.Category,y=Total_Profit,label =Total_Profit))+
labs(x = "Furnitures", y = "Total Profit", title = "Profitable Furnitures in California State")+
theme(axis.text = element_text(size = 10, face = "bold"), title = element_text(size = 16))+
theme(legend.title = element_text(size=10),legend.text = element_text(size=10),legend.position="bottom")
Profitable Furnitures in New Jersey
Superstore %>%
group_by(Sub.Category) %>%
filter(Category== "Furniture" & State== "New Jersey") %>%
summarise(Total_Profit= sum(Profit)) %>%
ggplot(aes(x= Sub.Category,y=Total_Profit, fill= Sub.Category))+
geom_col(width = 0.5, alpha = 0.5)+
geom_point(size=9, color="black",alpha=0.07)+
coord_flip()+
geom_text(aes(x= Sub.Category,y=Total_Profit,label =Total_Profit))+
labs(x = "Furnitures", y = "Total Profit", title = "Profitable Furnitures in New Jersey State")+
theme(axis.text = element_text(size = 10, face = "bold"), title = element_text(size = 16))+
theme(legend.title = element_text(size=10),legend.text = element_text(size=10),legend.position="bottom")
Profitable Furnitures in Connecticut
Superstore %>%
group_by(Sub.Category) %>%
filter(Category== "Furniture" & State== "Connecticut") %>%
summarise(Total_Profit= sum(Profit)) %>%
ggplot(aes(x= Sub.Category,y=Total_Profit, fill= Sub.Category))+
geom_col(width = 0.5, alpha = 0.5)+
geom_point(size=9, color="black",alpha=0.07)+
coord_flip()+
geom_text(aes(x= Sub.Category,y=Total_Profit,label =Total_Profit))+
labs(x = "Furnitures", y = "Total Profit", title = "Profitable Furnitures in Connecticut State")+
theme(axis.text = element_text(size = 10, face = "bold"), title = element_text(size = 16))+
theme(legend.title = element_text(size=10),legend.text = element_text(size=10),legend.position="bottom")
Profitable Furnitures in Wisconsin
Superstore %>%
group_by(Sub.Category) %>%
filter(Category== "Furniture" & State== "Wisconsin") %>%
summarise(Total_Profit= sum(Profit)) %>%
ggplot(aes(x= Sub.Category,y=Total_Profit, fill= Sub.Category))+
geom_col(width = 0.5, alpha = 0.5)+
geom_point(size=9, color="black",alpha=0.07)+
coord_flip()+
geom_text(aes(x= Sub.Category,y=Total_Profit,label =Total_Profit))+
labs(x = "Furnitures", y = "Total Profit", title = "Profitable Furnitures in Wisconsin State")+
theme(axis.text = element_text(size = 10, face = "bold"), title = element_text(size = 16))+
theme(legend.title = element_text(size=10),legend.text = element_text(size=10),legend.position="bottom")
Profitable Furnitures in Colorado
Superstore %>%
group_by(Sub.Category) %>%
filter(Category== "Furniture" & State== "Colorado") %>%
summarise(Total_Profit= sum(Profit)) %>%
ggplot(aes(x= Sub.Category,y=Total_Profit, fill= Sub.Category))+
geom_col(width = 0.5, alpha = 0.5)+
geom_point(size=9, color="black",alpha=0.07)+
coord_flip()+
geom_text(aes(x= Sub.Category,y=Total_Profit,label =Total_Profit))+
labs(x = "Furnitures", y = "Total Profit", title = "Profitable Furnitures in Colorado State")+
theme(axis.text = element_text(size = 10, face = "bold"), title = element_text(size = 16))+
theme(legend.title = element_text(size=10),legend.text = element_text(size=10),legend.position="bottom")
Profitable Technology in California
Superstore %>%
group_by(Sub.Category) %>%
filter(Category== "Technology" & State== "California") %>%
summarise(Total_Profit= sum(Profit)) %>%
ggplot(aes(x= Sub.Category,y=Total_Profit, fill= Sub.Category))+
geom_col(width = 0.5, alpha = 0.5)+
geom_point(size=9, color="black",alpha=0.07)+
theme_classic()+
coord_flip()+
geom_text(aes(x= Sub.Category,y=Total_Profit,label =Total_Profit))+
labs(x = "Technology", y = "Total Profit", title = "Profitable Technology in California State")+
theme(axis.text = element_text(size = 10, face = "bold"), title = element_text(size = 16))+
theme(legend.title = element_text(size=10),legend.text = element_text(size=10),legend.position="bottom")
Profitable Technology in New Jersey
Superstore %>%
group_by(Sub.Category) %>%
filter(Category== "Technology" & State== "New Jersey") %>%
summarise(Total_Profit= sum(Profit)) %>%
ggplot(aes(x= Sub.Category,y=Total_Profit, fill= Sub.Category))+
geom_col(width = 0.5, alpha = 0.5)+
geom_point(size=9, color="black",alpha=0.07)+
theme_classic()+
coord_flip()+
geom_text(aes(x= Sub.Category,y=Total_Profit,label =Total_Profit))+
labs(x = "Technology", y = "Total Profit", title = "Profitable Technology in New Jersey State")+
theme(axis.text = element_text(size = 10, face = "bold"), title = element_text(size = 16))+
theme(legend.title = element_text(size=10),legend.text = element_text(size=10),legend.position="bottom")
Profitable Technology in Connecticut
Superstore %>%
group_by(Sub.Category) %>%
filter(Category== "Technology" & State== "Connecticut") %>%
summarise(Total_Profit= sum(Profit)) %>%
ggplot(aes(x= Sub.Category,y=Total_Profit, fill= Sub.Category))+
geom_col(width = 0.5, alpha = 0.5)+
geom_point(size=9, color="black",alpha=0.07)+
theme_classic()+
coord_flip()+
geom_text(aes(x= Sub.Category,y=Total_Profit,label =Total_Profit))+
labs(x = "Technology", y = "Total Profit", title = "Profitable Technology in Connecticut State")+
theme(axis.text = element_text(size = 10, face = "bold"), title = element_text(size = 16))+
theme(legend.title = element_text(size=10),legend.text = element_text(size=10),legend.position="bottom")
Profitable Technology in Wisconsin
Superstore %>%
group_by(Sub.Category) %>%
filter(Category== "Technology" & State== "Wisconsin") %>%
summarise(Total_Profit= sum(Profit)) %>%
ggplot(aes(x= Sub.Category,y=Total_Profit, fill= Sub.Category))+
geom_col(width = 0.5, alpha = 0.5)+
geom_point(size=9, color="black",alpha=0.07)+
theme_classic()+
coord_flip()+
geom_text(aes(x= Sub.Category,y=Total_Profit,label =Total_Profit))+
labs(x = "Technology", y = "Total Profit", title = "Profitable Technology in Wisconsin State")+
theme(axis.text = element_text(size = 10, face = "bold"), title = element_text(size = 16))+
theme(legend.title = element_text(size=10),legend.text = element_text(size=10),legend.position="bottom")
Profitable Technology in Colorado
Superstore %>%
group_by(Sub.Category) %>%
filter(Category== "Technology" & State== "Colorado") %>%
summarise(Total_Profit= sum(Profit)) %>%
ggplot(aes(x= Sub.Category,y=Total_Profit, fill= Sub.Category))+
geom_col(width = 0.5, alpha = 0.5)+
geom_point(size=9, color="black",alpha=0.07)+
coord_flip()+
geom_text(aes(x= Sub.Category,y=Total_Profit,label =Total_Profit))+
labs(x = "Technology", y = "Total Profit", title = "Profitable Technology in Colorado State")+
theme(axis.text = element_text(size = 10, face = "bold"), title = element_text(size = 16))+
theme(legend.title = element_text(size=10),legend.text = element_text(size=10),legend.position="bottom")
Price per product in different Sub-Categories
List=list()
a=0
for (j in Superstore) {
a= (Superstore$Sales)/(Superstore$Quantity)
List[[length(List)+1]]=a
}
Superstore=Superstore %>% mutate(Price_per_product=as.integer(paste(a)))
product_price=Superstore %>%
group_by(Sub.Category) %>%
summarise(Total_Profit= sum(Price_per_product))%>%
arrange(desc(Total_Profit))
datatable(product_price)
ggplot(product_price, aes(x= Sub.Category,y=Total_Profit,fill= Sub.Category))+
geom_col(width = 0.5, alpha = 0.5)+
geom_point(size=9, color="black",alpha=0.07)+
theme_classic()+
coord_flip()+
geom_text(aes(x= Sub.Category,y=Total_Profit,label =Total_Profit))+
labs(x = "Sub.Category", y = "Total Profit", title = "Price per product in different Sub-Categories")+
theme(axis.text= element_text(size = 10, face = "bold"), title = element_text(size = 16))+
theme(legend.title = element_text(size=10),legend.text = element_text(size=10),legend.position="bottom")
Profit per product in different Sub-Categories
List_new=list()
b=0
for (i in Superstore) {
b= (Superstore$Profit)/(Superstore$Quantity)
List_new[[length(List_new)+1]]=b
}
Superstore=Superstore %>% mutate(Profit_per_product=as.integer(paste(b)))
product_profit=Superstore %>%
group_by(Sub.Category) %>%
summarise(Total_Product_Profit= sum(Profit_per_product))%>%
arrange(desc(Total_Product_Profit))
datatable(product_profit)
Plotting Profit per product in different Sub-Categories
ggplot(product_profit, aes(x= Sub.Category,y=Total_Product_Profit,fill= Sub.Category))+
geom_col(width = 0.5, alpha = 0.5)+
geom_point(size=9, color="black",alpha=0.07)+
coord_flip()+
geom_text(aes(x= Sub.Category,y=Total_Product_Profit,label =Total_Product_Profit))+
labs(x = "Sub.Category", y = "Total Product Profit", title = "Profit per product in different Sub-Categories")+
theme(axis.text= element_text(size = 10, face = "bold"), title = element_text(size = 16))+
theme(legend.title = element_text(size=10),legend.text = element_text(size=10),legend.position="bottom")
Superstore %>%
ggplot(aes(x=Ship.Mode,y=Profit,fill= Ship.Mode))+
geom_col(width = 0.5, alpha = 0.5)+
facet_wrap(~Region)+
theme_dark()+
coord_flip()+
labs(x = "Shipping Model", y = "Product Profit", title = "Shipping Models for Profit")+
theme(axis.text= element_text(size = 10, face = "bold"), title = element_text(size = 16))+
theme(legend.title = element_text(size=10),legend.text = element_text(size=10),legend.position="bottom")
Superstore %>%
ggplot(aes(x=Ship.Mode,y= Profit,,fill= Ship.Mode))+
geom_col(width = 0.5)+
facet_wrap(~Category)+
theme_dark()+
labs(x = "Shipping Model", y = "Product Profit", title = "Shipping Models for Profit")+
theme(axis.text= element_text(size = 12, face = "bold"), title = element_text(size = 16))+
theme(axis.text.x = element_text(angle = 90 ,size = 12, face = "bold"))+
theme(legend.title = element_text(size=10),legend.text = element_text(size=10),legend.position="bottom")
Superstore %>%
ggplot(aes(x=Ship.Mode,y= Profit,,fill= Ship.Mode))+
geom_col(width = 0.5)+
facet_wrap(~Sub.Category)+
theme_dark()+
labs(x = "Shipping Model", y = "Product Profit", title = "Shipping Models for Profit")+
theme(axis.text= element_text(size = 12, face = "bold"), title = element_text(size = 16))+
theme(axis.text.x = element_text(angle = 90 ,size = 12, face = "bold"))+
theme(legend.title = element_text(size=10),legend.text = element_text(size=10),legend.position="bottom")
Superstore %>%
ggplot(aes(x=Ship.Mode,y=Profit,fill= Ship.Mode))+
geom_col(width = 0.5, alpha = 0.5)+
facet_wrap(~Segment)+
theme_dark()+
coord_flip()+
labs(x = "Shipping Model", y = "Product Profit", title = "Shipping Models for Profit")+
theme(axis.text= element_text(size = 10, face = "bold"), title = element_text(size = 16))+
theme(legend.title = element_text(size=10),legend.text = element_text(size=10),legend.position="bottom")
Superstore %>%
ggplot(aes(x=Ship.Mode,y=Quantity,fill= Ship.Mode))+
geom_col(width = 0.5, alpha = 0.5)+
facet_wrap(~Region)+
theme_dark()+
coord_flip()+
labs(x = "Shipping Model", y = "Product Quantity", title = "Shipping Models for Quantity")+
theme(axis.text= element_text(size = 10, face = "bold"), title = element_text(size = 16))+
theme(legend.title = element_text(size=10),legend.text = element_text(size=10),legend.position="bottom")
Superstore %>%
ggplot(aes(x=Ship.Mode,y=Quantity,,fill= Ship.Mode))+
geom_col(width = 0.5)+
facet_wrap(~Category)+
theme_dark()+
labs(x = "Shipping Model", y = "Product Quantity", title = "Shipping Models for Quantity")+
theme(axis.text= element_text(size = 12, face = "bold"), title = element_text(size = 16))+
theme(axis.text.x = element_text(angle = 90 ,size = 12, face = "bold"))+
theme(legend.title = element_text(size=10),legend.text = element_text(size=10),legend.position="bottom")
Superstore %>%
ggplot(aes(x=Ship.Mode,y=Quantity,,fill= Ship.Mode))+
geom_col(width = 0.5)+
facet_wrap(~Sub.Category)+
theme_dark()+
labs(x = "Shipping Model", y = "Product Quantity", title = "Shipping Models for Quantity")+
theme(axis.text= element_text(size = 12, face = "bold"), title = element_text(size = 16))+
theme(axis.text.x = element_text(angle = 90 ,size = 12, face = "bold"))+
theme(legend.title = element_text(size=10),legend.text = element_text(size=10),legend.position="bottom")
Superstore %>%
ggplot(aes(x=Ship.Mode,y=Quantity,fill= Ship.Mode))+
geom_col(width = 0.5, alpha = 0.5)+
facet_wrap(~Segment)+
theme_dark()+
coord_flip()+
labs(x = "Shipping Model", y = "Product Quantity", title = "Shipping Models for Quantity")+
theme(axis.text= element_text(size = 10, face = "bold"), title = element_text(size = 16))+
theme(legend.title = element_text(size=10),legend.text = element_text(size=10),legend.position="bottom")
Superstore %>%
ggplot(aes(x=Ship.Mode,y=Sales,fill= Ship.Mode))+
geom_col(width = 0.5, alpha = 0.5)+
facet_wrap(~Region)+
theme_dark()+
coord_flip()+
labs(x = "Shipping Model", y = "Product Sales", title = "Shipping Models for Sales")+
theme(axis.text= element_text(size = 10, face = "bold"), title = element_text(size = 16))+
theme(axis.text.x = element_text(angle = 90 ,size = 12, face = "bold"))+
theme(legend.title = element_text(size=10),legend.text = element_text(size=10),legend.position="bottom")
Superstore %>%
ggplot(aes(x=Ship.Mode,y=Sales,,fill= Ship.Mode))+
geom_col(width = 0.5)+
facet_wrap(~Category)+
theme_dark()+
labs(x = "Shipping Model", y = "Product Sales", title = "Shipping Models for Sales")+
theme(axis.text= element_text(size = 12, face = "bold"), title = element_text(size = 16))+
theme(axis.text.x = element_text(angle = 90 ,size = 12, face = "bold"))+
theme(legend.title = element_text(size=10),legend.text = element_text(size=10),legend.position="bottom")
Superstore %>%
ggplot(aes(x=Ship.Mode,y=Sales,,fill= Ship.Mode))+
geom_col(width = 0.5)+
facet_wrap(~Sub.Category)+
theme_dark()+
labs(x = "Shipping Model", y = "Product Sales", title = "Shipping Models for Sales")+
theme(axis.text= element_text(size = 12, face = "bold"), title = element_text(size = 16))+
theme(axis.text.x = element_text(angle = 90 ,size = 12, face = "bold"))+
theme(legend.title = element_text(size=10),legend.text = element_text(size=10),legend.position="bottom")
Superstore %>%
ggplot(aes(x=Ship.Mode,y=Sales,fill= Ship.Mode))+
geom_col(width = 0.5, alpha = 0.5)+
facet_wrap(~Segment)+
theme_dark()+
coord_flip()+
labs(x = "Shipping Model", y = "Product Sales", title = "Shipping Models for Sales")+
theme(axis.text= element_text(size = 10, face = "bold"), title = element_text(size = 16))+
theme(legend.title = element_text(size=10),legend.text = element_text(size=10),legend.position="bottom")
Superstore$DiscountedPrice= Superstore$Sales- (Superstore$Sales*Superstore$Discount)
Superstore$Sales_Quantity= Superstore$Sales/Superstore$Quantity
Superstore$DP_Quantity= Superstore$DiscountedPrice/Superstore$Quantity
View(Superstore)
No_Discount=Superstore%>%
filter(Discount==0.00) %>%
summarise(Total_Quantity= sum(Quantity))
datatable(No_Discount)
Discount=Superstore%>%
filter(Discount!=0.00) %>%
summarise(Total_Quantity= sum(Quantity))
datatable(Discount)
Total_Quantity=Discount- No_Discount
datatable(Total_Quantity)